scholarly journals Image watermarking based on integer wavelet transform-singular value decomposition with variance pixels

2019 ◽  
Vol 9 (3) ◽  
pp. 2185 ◽  
Author(s):  
Ferda Ernawan ◽  
Dhani Ariatmanto
Keyword(s):  
Wavelet Transform ◽  
Singular Value Decomposition ◽  
Image Watermarking ◽  
Threshold Value ◽  
Singular Value ◽  
Multimedia Data ◽  
Optimal Threshold ◽  
Integer Wavelet Transform ◽  
Value Decomposition ◽  
Integer Wavelet

With the era of rapid technology in multimedia, the copyright protection is very important to preserve an ownership of multimedia data. This paper proposes an image watermarking scheme based on Integer Wavelet Transform (IWT) and Singular Value Decomposition (SVD). The binary watermark is scrambled by Arnold transform before embedding watermark. Embedding locations are determined by using variance pixels. Selected blocks with the lowest variance pixels are transformed by IWT, thus the LL sub-band of 8×8 IWT is computed by using SVD. The orthogonal U matrix component of U3,1 and U4,1 are modified using certain rules by considering the watermark bits and an optimal threshold. This research reveals an optimal threshold value based on the trade-off between robustness and imperceptibility of watermarked image. In order to measure the watermarking performance, the proposed scheme is tested under various attacks. The experimental results indicate that our scheme achieves higher robustness than other scheme under different types of attack.

scholarly journals A multi-scale image watermarking based on integer wavelet transform and singular value decomposition

2020 ◽  
pp. 114272
Author(s):  
Yuling Luo ◽  
Liangjia Li ◽  
Junxiu Liu ◽  
Shunbin Tang ◽  
Lvchen Cao ◽  
...  
Keyword(s):  
Wavelet Transform ◽  
Singular Value Decomposition ◽  
Image Watermarking ◽  
Singular Value ◽  
Integer Wavelet Transform ◽  
Multi Scale ◽  
Value Decomposition ◽  
Integer Wavelet

scholarly journals Comparative analysis of medical images watermarking methods

2020 ◽  
Vol 17 ◽  
pp. 379-383
Author(s):  
Sylwia Duda ◽  
Dominik Fijałek ◽  
Grzegorz Kozieł
Keyword(s):  
Wavelet Transform ◽  
Comparative Analysis ◽  
Singular Value Decomposition ◽  
Discrete Cosine Transform ◽  
Medical Images ◽  
Singular Value ◽  
Integer Wavelet Transform ◽  
Cosine Transform ◽  
Value Decomposition ◽  
Integer Wavelet

The article is devoted to the analysis of watermarking algorithms in terms of their use in marking medical images. The algorithms based on the Integer Wavelet Transform (IWT), Discrete Cosine Transform (DCT), and Singular Value Decomposition (SVD) were compared. The algorithms were implemented using the combinations: IWT, IWT-DCT, and IWT-SVD. As part of the research, the level of disturbances caused by embedding the watermark was checked using subjective and objective methods. The attack resistance of the watermarked images was tested and the steganographic capacity was measured. All algorithms are based on IWT, however, each has different advantages. The algorithm based on the IWT showed the highest capacity. The most resistant to attacks is IWT-SVD, and the lowest level of interference was obtained for the IWT-DCT algorithm.

Image Steganography Using Integer Wavelet Transform and Singular Value Decomposition

2019 ◽  
Vol 7 (3) ◽  
pp. 967-971
Author(s):  
Shaik Shabina ◽  
Ravipati Iswarya Lakshmi ◽  
Shaik Arshia ◽  
Vemuri Harshitha ◽  
Rayachoti Eswariah
Keyword(s):  
Wavelet Transform ◽  
Singular Value Decomposition ◽  
Singular Value ◽  
Image Steganography ◽  
Integer Wavelet Transform ◽  
Value Decomposition ◽  
Integer Wavelet

LWT-DCT based Image Watermarking Scheme using Normalized SVD

2020 ◽  
Vol 13 ◽  
Author(s):  
Rahul Dixit ◽  
Amita Nandal ◽  
Arvind Dhaka ◽  
Vardan Agarwal ◽  
Yohan Varghese
Keyword(s):  
Wavelet Transform ◽  
Singular Value Decomposition ◽  
Discrete Cosine Transform ◽  
Image Watermarking ◽  
Singular Value ◽  
Cover Image ◽  
Lifting Wavelet Transform ◽  
Cosine Transform ◽  
Lifting Wavelet ◽  
Value Decomposition

Background: Nowadays information security is one of the biggest issues of social networks. The multimedia data can be tampered with, and the attackers can then claim its ownership. Image watermarking is a technique that is used for copyright protection and authentication of multimedia. Objective: We aim to create a new and more robust image watermarking technique to prevent illegal copying, editing and distribution of media. Method : The watermarking technique proposed in this paper is non-blind and employs Lifting Wavelet Transform on the cover image to decompose the image into four coefficient matrices. Then Discrete Cosine Transform is applied which separates a selected coefficient matrix into different frequencies and later Singular Value Decomposition is applied. Singular Value Decomposition is also applied to the watermarking image and it is added to the singular matrix of the cover image which is then normalized followed by the inverse Singular Value Decomposition, inverse Discrete Cosine Transform and inverse Lifting Wavelet Transform respectively to obtain an embedded image. Normalization is proposed as an alternative to the traditional scaling factor. Results: Our technique is tested against attacks like rotation, resizing, cropping, noise addition and filtering. The performance comparison is evaluated based on Peak Signal to Noise Ratio, Structural Similarity Index Measure, and Normalized Cross-Correlation. Conclusion: The experimental results prove that the proposed method performs better than other state-of-the-art techniques and can be used to protect multimedia ownership.

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